1. Field of the Invention
The present invention relates to an image processing technique for automatically and accurately detecting an anatomical configuration from a (PA: postero-anterior) digitized chest radiograph, which is necessary for the computer-aided diagnosis of the chest, and in particular, to an image processing technique that makes it possible to, with higher precision, detect the boundary of a ribcage from a digitized chest radiograph.
2. Description of the Related Art
Digitized chest radiographs have been widely used in the field of computer-aided diagnosis. A wide variety of types of computer-aided diagnosis which is capable of automatically detecting ribcage boundary information and landmark information both specifying anatomical configurations of the chest have been known. One conventional technique is provided by “Xin-Wei Xu and Kunio Doi, Image feature analysis for computer-aided diagnosis: Accurate determination of ribcage boundary in chest radiographs, Med. Phys. 22(5), May 1995.” This technique is also provided by Japanese Patent Laid-open Publication NO.7-37074.
This diagnostic technique uses lesion-enhanced images in order to detect the temporal changes of diseases such as lung diseases from digitized chest radiographs which are acquired at different times for the same patient's region. To increase diagnostic accuracy, this technique comprises the steps of obtaining previous and current digital chest images, positioning both the previous and current digital images by performing a non-linear warping processing based on a non-linear warping technique on either the previous or current digital image, and making a subtraction between the previous and current image, one of which having undergone the non-linear warping. The non-linear warping technique uses information that is detected from a chest image in relation to its anatomical structure and is based on a local matching technique to be applied to a number of tiny regions of interest (ROIs) which are selected based on the detected information. The non-linear warping technique is a mapping of amounts of matching shift obtained between corresponding locations in two frames of images. The mapping is realized by using amounts of local matching resulting from a local matching technique which is applied to the locations and a weighted fitting technique which uses weights resulting from image data analysis that is applied to the ROIs. In addition, the mapping of shift amounts is based on two-dimensional polynomial functions which are fitted to shift values.
However, the above-described conventional automatic detection technique tends to fail in the detection of boundary candidate points if contrast is low in the vicinity of a ribcage boundary. If such a failure occurs, the ribcage boundary, which is acquired by approximating the boundary candidate points to polynomials, deviates from the true ribcage boundary. This reduces the accuracy in computer-aided diagnosis as a whole.
In addition, when a searching ROI is designated with a diaphragm which is included in the region, the boundary candidate points are pulled toward structures within the lung views. The boundary candidate points are difficult to be detected on the true ribcage boundary. This results in a lowered accuracy in computer-aided diagnosis as well.
Further, in cases where a top lung is depicted in high contrast on a chest image, the detected boundary candidate points are pulled toward the ribs, clavicles, lesions, and/or others residing within the lung views. In this case, the upper ribcage boundary candidate points will not be detected on the true upper ribcage boundary, thereby leading to a lowered accuracy in computer-aided diagnosis.
Still further, if a searching ROI to search an upper ribcage boundary is designated so as not to cross the true ribcage boundary, then the boundaries of chest structures (the ribs, clavicles, lesions, scapulas, and/or others) other than the original true boundary are detected. This also deteriorates computer-aided diagnosis in accuracy.
For using features of a chest image and positional information which are indicative of an anatomical structure in computer-aided diagnosis, it is significant to acquire more accurate information about a ribcage boundary and landmarks. It has therefore been strongly desired that more accurate information be available for computer-aided diagnosis.